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Welcome! This is a short overview of the Metrici MidSYS-AI โ€” the mid-range tier of the Metrici AI Server family. It is a pre-configured, on-premise appliance that ships with Ubuntu and the Metrici detection engines already installed. This page covers the key specifications, where the model fits in the lineup, what it runs, and how to bring it online.

Table of Contents

  1. Introduction
  2. Technical Data
  3. What It Runs
  4. Setup & Operation
  5. Support & Resources

1. Introduction

The Metrici MidSYS-AI is a balanced, mid-range AI server built to run Metriciโ€™s deep neural network engines in real time. It is designed for growing operations โ€” sites that have outgrown a single-camera edge device but do not yet need a rack-mounted, multi-GPU platform.

The unit is delivered as a ready-to-use appliance: the operating system and Metrici engines are pre-installed, so no software setup is required on site. The engines are then customised for the specific deployment โ€” adding cameras, configuring detection parameters, and completing setup in the Metrici Web Interface. All processing happens locally on the unit; no data has to leave your premises.

At a Glance

Processor
Intelยฎ Coreโ„ข Ultra 5 245K ยท 4.2 GHz
Cores / Threads
14 cores (6P + 8E) ยท 14 threads
AI Accelerator
Intelยฎ AI Boost NPU ยท up to 13 TOPS (INT8)
Camera Capacity
Up to 8 cameras
Memory / Storage
16 GB DDR5 ยท 500 GB SSD
Operating System
Ubuntu 24.04 LTS

The Server Range

Metrici AI Servers come in four tiers, from a compact edge device to a data-center-scale platform. MidSYS-AI sits in the mid-range โ€” the natural step up for small business, retail, and lighter industrial deployments.

MicroSYS
โ†’
MidSYS
โ†’
HighSYS
โ†’
UltraSYS

Each tier is pre-validated with Metrici software before delivery, and the architecture is designed to scale โ€” you can move up to a higher tier as a deployment grows. If you are unsure which model fits, Metriciโ€™s team sizes the system based on your cameras, engines, and expected workload.

2. Technical Data

The full specification of the MidSYS-AI as delivered:

SpecificationDetails
ArchitectureIntel x86_64
Processor (CPU)1 × Intelยฎ Coreโ„ข Ultra 5 245K, 4.2 GHz
Processing units14 cores (6 P-cores + 8 E-cores) / 14 threads
AI accelerator1 × Intelยฎ AI Boost NPU (integrated), up to 13 TOPS (INT8)
PerformanceUp to 8 cameras, depending on workload type
RAM memory16 GB DDR5
Storage500 GB SSD
Networking1 × Ethernet 10 / 100 / 1000 Mbps
GraphicsIntegrated Intelยฎ Graphics (4 Xe-cores), HDMI output
FormatCube case, 34 × 32 × 43 cm
Power source1 × 850 W
Operating systemLinux Ubuntu 24.04 LTS
Note: AI acceleration on the MidSYS-AI is provided by the integrated Intelยฎ AI Boost NPU together with the Intelยฎ Xe graphics cores โ€” there is no separate add-in GPU. Sustained camera throughput depends on the mix of engines running; see the next chapter.

3. What It Runs

The MidSYS-AI is configured to run any combination of Metrici detection engines at the same time. Common engines include:

The unit supports up to 8 cameras. The exact number it can drive comfortably depends on the engine mix, frame rates, and detection load โ€” a single light engine reaches the upper figure more easily than several heavy engines running together.

Sizing tip: If you are planning several engines on the same unit, share your camera count, engine list, and expected traffic with Metrici. The team will confirm whether MidSYS-AI is the right tier or recommend a step up.

4. Setup & Operation

The MidSYS-AI arrives ready to use. To bring it online for the first time:

  1. Place the unit on a clean, flat, well-ventilated surface (see Placement).
  2. Connect the network cable to the Ethernet port.
  3. Connect a display to the HDMI output if needed. The unit can also run headless.
  4. Connect the unit to mains power using the supplied power cable, then switch on the power supply.
  5. Power the unit on.

The operating system completes boot within roughly 30โ€“60 seconds, and the Metrici engines start automatically as background services. The unitโ€™s IP address is either pre-configured by Metrici before shipping (documented in the delivery note) or obtained from your network by DHCP. From there, configuration is completed in the Metrici Web Interface.

Placement & Ventilation

Install the unit on a stable surface in a well-ventilated area, away from direct sunlight, heat sources, and high-dust environments. Leave clearance around the chassis so air can move freely through the vents, and avoid enclosed cabinets without active ventilation.

Important! Do not block the chassis vents. Operating the server with restricted airflow will cause the processor to thermally throttle โ€” reducing performance โ€” and may shorten product lifetime.

5. Support & Resources

For configuration help, system sizing, or a quote for the right server tier, contact the Metrici team. The product datasheet and CE declaration are linked in the sidebar under Resources.